Statistical classification of South African seasonal divisions on the basis of daily temperature data

Abstract

Across South Africa, a wide range of activities is influenced by differences in seasonality. In a South African context, there is little consensus on the timing of seasonal boundaries. Inconsistency exists through the use of ad-hoc approaches to define seasonal boundaries across South Africa. In this paper, we present one of the very first uniform statistical classifications of South African seasonal divisions on the basis of daily temperature data. Daily maximum and minimum temperature data were obtained from 35 selected South African Weather Service meteorological stations that had sufficiently complete data sets and homogeneous time series, spanning the period 1980–2015. An Euclidean cluster analysis was performed using Ward’s D method. We found that the majority of the stations can be classified into four distinct seasons, with the remaining 12 stations’ data best classified into three seasons, using Tavg as the classifier. The statistically classified seasonal brackets include summer (October/November/December/ January/February/March), early autumn (April) and late autumn (May), winter (June/July/August), and spring (September). Exploring the boundaries of seasons, the start of summer and end of winter months follow a southwest to northeastwards spatial pattern across the country. Summers start later and winters end later in the southwestern parts of the country, whereas in the northeast, summers start earlier and winters end earlier. Significance: • The findings contribute to the common knowledge of seasonality in South Africa. • New seasonal divisions in South Africa are proposed.

Keywords

• seasonality
• classification
• climatology
• biometeorology
• Euclidean cluster analysis